This is the README file for the replication materials associated with:

Caleb Pomeroy, "Correspondence: Measuring Power in International Relations," International Security, Vol. 44, No. 1 (Summer 2019). 

The letter contains two applications: (1) a reanalysis of the AIC improvements reported in Michael Beckley, "The Power of Nations: Measuring What Matters," International Security, Vol. 43, No. 2 (Fall 2018), pp. 7–44, doi:10.1162/ISEC_a_00328, and (2) a reestimation of relevant models reported during the article's replication exercises.  

The first section of the R code file "beckley_rep.R" contains the code associated with Application ONE. The CSV file "beckley_aic_table.csv" contains the underlying replication information (i.e. the AIC numbers) reported in Table 3 of the Appendix associated with "The Power of Nations."  

The second section of the R code file "beckley_rep.R" contains the code associated with Application TWO. This application reestimates the models from the replication exercises in "The Power of Nations" that included a linear term (i.e. the original study employed only a first order GDP or CINC term to operationalize power). The original GDP or CINC term is replaced with Beckley's proposed GDPxGDPPC (as done in "The Power of Nations") and those AICs are compared to two alternative specifications to check for "better" ways to specify the variable in a regression using AIC as our metric of interest. 

The first alternative specification consists of the square root of GDPxGDPPC + GDPxGDPPC. Since GDP-squared is very large relative to population, GDPxGDPPC acts very much like a quadratic term. Thus, the square root of the proposed variable provides a rough first order version of the variable. The second alternative specification consists of population + GDP + GDP-squared. This model represents a more traditional specification of the underlying variables of interest (i.e. population and GDP, with a hypothesized quadratic effect on GDP). The motivation behind this exercise is as follows: if one wants to employ the proposed variable in a regression, how might we "best" model the variable's theoretical intuition?

The file "power2.tab" contains Beckley's proposed variable, and the following files provide the underlying data for the replicated studies:

Allen_DiGi_Rep.tab
Colgan.tab
GH_SS_Replication.tab
HorowitzStamLeadersIOMIDReplication.tab
NarangTalmadge.tab


Please feel free to reach out with any questions. 

Caleb Pomeroy
pomeroy.38@osu.edu
Department of Political Science
The Ohio State University
